CN112396041A - Road marking alignment system based on image recognition - Google Patents
Road marking alignment system based on image recognition Download PDFInfo
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- CN112396041A CN112396041A CN202110065806.9A CN202110065806A CN112396041A CN 112396041 A CN112396041 A CN 112396041A CN 202110065806 A CN202110065806 A CN 202110065806A CN 112396041 A CN112396041 A CN 112396041A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/35—Categorising the entire scene, e.g. birthday party or wedding scene
- G06V20/38—Outdoor scenes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/30—Noise filtering
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Abstract
The invention relates to a road marking alignment system based on image recognition, which consists of an upper computer, a control system and an image acquisition device; the image acquisition device comprises a camera, a sliding table, an inclined block, a light source and a mounting seat, wherein the front end of the light source is hinged with the mounting seat through a rotating shaft, the rear end of the camera is matched with the inclined block, and the light source and the camera are relatively fixed and arranged in the same direction for acquiring road marking images; the utility model discloses a camera shooting angle adjustment, including camera and control system, camera and upper computer connection for upload the image of gathering to the host computer and accomplish image processing, the host computer is connected with control system and is used for issuing the image processing result, control system drives according to the image processing result the slip table, the sloping block round trip movement is used for promoting the light source to revolute the axle and is the every single move regulation under the drive of slip table, and this scheme liberates the manpower on camera shooting angle adjustment, makes the angle of adjustment at every turn controllable, resists the interference of bad weather to the installation, improves the installation effectiveness.
Description
Technical Field
The invention relates to the field of road marking detection, in particular to a road marking alignment system based on image recognition.
Background
The road marking is a traffic safety facility composed of various lines, arrows, characters, elevation marks, raised road signs, contour marks and the like marked on the road surface, and has the function of controlling and guiding traffic. The road marking is a traffic safety facility composed of various road surface markings, arrows, characters, elevation marks, raised road signs, road side line delineators and the like. It can be used in conjunction with road traffic signs or used alone. The accuracy of the road markings is very important since they are mainly used to guide vehicles, and in practice, the road markings are easily worn and require regular maintenance, and how to detect the markings is a major problem at present. Because the detection to the road marking needs to find a certain angle with the road marking to be detected, the traditional mode is manual debugging, not only occupies manpower, but also reduces the detection efficiency.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a road marking alignment system based on image recognition, which relieves manpower on camera shooting angle adjustment, enables the angle of each adjustment to be controllable, resists the interference of severe weather on installation and improves the installation efficiency.
The purpose of the invention is realized by the following technical scheme:
a road marking alignment system based on image recognition is composed of an upper computer, a control system and an image acquisition device;
the image acquisition device comprises a camera, a sliding table, an inclined block and a light source, wherein the front end of the light source is hinged through a rotating shaft, the rear end of the camera is matched with the inclined block, and the light source and the camera are relatively fixed and arranged in the same direction for acquiring a road marking image;
the camera is connected with the upper computer and used for uploading collected images to the upper computer to complete image processing, the upper computer is connected with the control system and used for issuing image processing results, the control system drives the sliding table according to the image processing results, and the inclined block moves back and forth under the driving of the sliding table and is used for pushing the light source to rotate around the rotating shaft to be adjusted in a pitching mode.
Furthermore, the inclined block is U-shaped, two sides of the inclined block are respectively provided with a waist-shaped hole which is obliquely arranged, two sides of the rear end of the light source are respectively fixed with a cam follower, and the cam followers are respectively positioned in the waist-shaped holes on the side where the cam followers are positioned.
Further, the light source, the sliding table, the inclined block and the camera are respectively arranged on a mounting seat, wherein the light source is hinged to the front end of the mounting seat through a rotating shaft.
Further, the camera is fixed under the light source through an L-shaped connecting piece.
Furthermore, a door-shaped support frame is arranged at the front end of the mounting seat, and the light source is hinged to the door-shaped support frame through a rotating shaft.
Further, the sliding table is driven by a stepping motor, and the stepping motor drives the sliding table under the control of the control system.
Further, the image processing comprises the steps of:
s100: acquiring an image;
s200: the filtering process comprises median filtering and mean filtering;
median filtering:
the original image and the processed image are respectively, W is a two-dimensional template, i.e. a two-dimensional matrix, where the original image only represents one image, and if necessary, the original image can be regarded as a difference image between a polished image and a non-polished image, i.e. the original image is a non-polished image, and the processed image is a polished image.
And (3) mean filtering:
respectively an original image and a processed image, wherein W is a two-dimensional template;
s300: threshold segmentation:
f (T) is the gray value of each pixel point after division, T is the gray value of each pixel point before division, and T is a set threshold;
s400: morphological transformation:
(a) and (3) shrinking:
r' denotes the row vectors of the reduced image matrix, R denotes the row vectors of the pre-reduction image matrix, MrowA reduction matrix representing a row direction; c' denotes the column vector of the image matrix after reduction, C denotes the column vector of the image matrix before reduction, McolA reduction matrix representing a column direction;
(b) translation:
g' represents a matrix of the translated image, CfRepresenting a translation matrix, F representing a matrix of the image before translation;
s500: positioning road marking;
processing the image by S300, acquiring points with the processed gray value of 255, namely pixel points of the road marking in the image, acquiring the gray average value of the road marking from the image before processing according to the row and column coordinates of the points, simultaneously taking the center coordinates of the points as the position of the road marking in the image, traversing the stroke of the stepping motor, acquiring the gray values of all the road markings in the range, recording the gray values and the position of the road marking in the image, and acquiring the position with the maximum gray value by sequencing.
Further, the step of acquiring the image comprises:
s101: the method comprises the following steps of (1) performing compensation polishing on a road marking line by using a light source;
s102: rapidly acquiring two images which are polished and not polished at the same time;
s103: the interference of other light sources is suppressed,
g is an image after suppressing interference of other light sources, F1For the first image, F2The second image, the first image is a glossy image and the second image is a matte image.
Further, the control system acquires the position of the road marking according to the image processing result, and controls the stepping motor to drive the sliding table to enable the camera to be aligned with the position of the road marking.
The invention has the beneficial effects that:
1. the invention solves the problem that the camera is difficult to align the road marking by combining the road marking identification with the image target positioning;
2. the method solves the problem of more interference of the image on the positioning of the road marking by combining the searching of the brightest position (the position with the maximum gray scale) of the road marking with a stepping motor system;
3. the invention solves the problem that the angle accuracy is difficult to ensure in the angle problem of the camera and the road marking by manual adjustment by combining the road marking alignment with the machine vision;
4. the invention solves the problems of low precision and low efficiency in severe weather in the problem of manually adjusting the angle between the camera and the road marking by combining the road marking alignment with the stepping motor system.
Drawings
FIG. 1 is a functional block diagram of the present invention;
FIG. 2 is a schematic view of an image capturing device according to the present invention;
FIG. 3 is a schematic view of an image processing flow;
FIG. 4 is a schematic view of a stepper motor control;
FIG. 5 is a schematic view of image acquisition;
FIG. 6 is a flow chart of road marking positioning.
Detailed Description
The technical solution of the present invention is further described in detail with reference to the following specific examples, but the scope of the present invention is not limited to the following.
A road marking alignment system based on image recognition is composed of an upper computer, a control system and an image acquisition device, and the whole working principle of the system can be shown in figure 1.
As shown in fig. 2, the image acquisition device comprises a light source 1, a sliding table 2, an inclined block 4, a camera 8 and a mounting seat 6, wherein the front end of the light source 1 is hinged with the mounting seat 6 through a rotating shaft 5, the rear end of the light source 1 is matched with the inclined block 4, and the camera 8 and the light source 1 are relatively fixed and arranged in the same direction for acquiring road marking images; the camera 8 is connected with an upper computer and used for uploading collected images to the upper computer to complete image processing, the upper computer is connected with the control system and used for issuing an image processing result, the control system drives the sliding table 2 according to the image processing result, and the inclined block 4 moves back and forth under the driving of the sliding table 2 and is used for pushing the light source 1 to perform pitching adjustment around the rotating shaft 5.
Optionally, in the road marking alignment system based on image recognition, the oblique block 4 is U-shaped, two oblique waist-shaped holes 3 are respectively formed in two sides of the oblique block, two cam followers 9 are respectively fixed on two sides of the rear end of the light source 1, and the cam followers 9 are respectively located in the waist-shaped holes 3 on the side where the cam followers are located.
Optionally, in the road marking alignment system based on image recognition, the camera 8 is fixed right below the light source 1 through an L-shaped connector.
Optionally, in the road marking alignment system based on image recognition, a door-shaped support frame 7 is arranged at the front end of the mounting seat 6, and the light source 1 is hinged to the door-shaped support frame 7 through the rotating shaft 5.
Optionally, in the road marking alignment system based on image recognition, the sliding table 2 is driven by a stepping motor, and the stepping motor drives the sliding table 2 under the control of the control system.
Referring to fig. 3, optionally, the step of image processing of a road marking alignment system based on image recognition is:
s100: acquiring an image;
s200: the filtering process comprises median filtering and mean filtering;
median filtering:
respectively an original image and a processed image, wherein W is a two-dimensional template;
and (3) mean filtering:
respectively an original image and a processed image, wherein W is a two-dimensional template;
the median filtering and the mean filtering are well known in the art, and the definition of each function in the formula involved is well known in the art.
S300: threshold segmentation:
f (T) is the gray value of each pixel point after division, T is the gray value of each pixel point before division, and T is a set threshold;
s400: morphological transformation:
(a) and (3) shrinking:
r' denotes the row vectors of the reduced image matrix, R denotes the row vectors of the pre-reduction image matrix, MrowA reduction matrix representing a row direction; c' denotes the column vector of the image matrix after reduction, C denotes the column vector of the image matrix before reduction, McolA reduction matrix representing a column direction;
(b) translation:
g' represents a matrix of the translated image, CfRepresenting a translation matrix, F representing a matrix of the image before translation;
s500: positioning road marking;
processing the image through S300, obtaining points with the processed gray value of 255, namely pixel points of the road marking in the image, obtaining the gray average value of the road marking from the image before processing according to the row and column coordinates of the points, meanwhile, taking the center coordinates of the points as the positions of the road marking in the image, traversing the stroke of the stepping motor, obtaining the gray values of all the road markings in the range, recording the gray values and the positions of the road markings in the image, obtaining the position with the maximum gray value through sorting, and the process is shown in FIG. 6.
Referring to fig. 5, in an alternative embodiment, the step of acquiring an image includes:
s101: using a camera 8 to perform compensation polishing on the road marking;
s102: rapidly acquiring two images which are polished and not polished at the same time;
s103: the interference of other light sources is suppressed,
g is an image after suppressing interference of other light sources, F1For the first image, F2The second image.
Optionally, in the road marking alignment system based on image recognition, the control system obtains the position of the road marking according to the result of image processing, and controls the stepping motor to drive the sliding table 2 so that the camera 8 is aligned with the position of the road marking, and the flow is shown in fig. 4.
Firstly, obtaining the position and the gray scale of a road marking, judging whether a motor reaches a positive line limit, if so, reversely moving a stepping motor, if not, positively moving the stepping motor until the motor reaches the positive line limit, then reversely moving the stepping motor, then obtaining the position and the gray scale of the road marking, judging whether the stepping motor reaches a negative line limit, and if not, continuously reversely moving the stepping motor until the stepping motor reaches the negative line limit.
The foregoing is illustrative of the preferred embodiments of this invention, and it is to be understood that the invention is not limited to the precise form disclosed herein and that various other combinations, modifications, and environments may be resorted to, falling within the scope of the concept as disclosed herein, either as described above or as apparent to those skilled in the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. A road marking alignment system based on image recognition is characterized by comprising an upper computer, a control system and an image acquisition device;
the image acquisition device comprises a light source (1), a sliding table (2), an inclined block (4) and a camera (8), wherein the front end of the light source (1) is hinged through a rotating shaft (5), the rear end of the light source (1) is matched with the inclined block (4), and the camera (8) and the light source (1) are relatively fixed and arranged in the same direction to acquire a road marking image;
camera (8) and upper computer connection for upload the image of gathering to the host computer completion image processing, the host computer is connected with control system and is used for issuing the image processing result, control system drives according to the image processing result slip table (2), sloping block (4) round trip movement is used for promoting light source (1) to do every single move and adjust around pivot (5) under the drive of slip table (2).
2. The image recognition-based road marking alignment system according to claim 1, wherein the inclined block (4) is U-shaped, two sides of the inclined block are respectively provided with an obliquely arranged waist-shaped hole (3), two sides of the rear end of the light source (1) are respectively fixed with a cam follower (9), and the cam followers (9) are respectively positioned in the waist-shaped holes (3) on the sides.
3. The image recognition-based road marking alignment system according to claim 2, wherein the light source (1), the sliding table (2), the inclined block (4) and the camera (8) are respectively mounted on a mounting seat (6), and the light source (1) is hinged to the front end of the mounting seat (6) through the rotating shaft (5).
4. The image recognition-based road marking alignment system according to claim 3, wherein the camera (8) is fixed directly below the light source (1) through an L-shaped connecting piece.
5. The image recognition-based road marking alignment system according to claim 4, wherein a door-shaped support frame (7) is arranged at the front end of the mounting seat (6), and the light source (1) is hinged on the door-shaped support frame (7) through a rotating shaft (5).
6. An image recognition-based road marking alignment system as claimed in claim 5, wherein the slide table (2) is driven by a stepping motor, and the stepping motor drives the slide table (2) under the control of the control system.
7. The system of claim 6, wherein the image processing comprises:
s100: acquiring an image;
s200: the filtering process comprises median filtering and mean filtering;
median filtering:
respectively an original image and a processed image, wherein W is a two-dimensional template;
and (3) mean filtering:
respectively an original image and a processed image, wherein W is a two-dimensional template;
s300: threshold segmentation:
f (T) is the gray value of each pixel point after division, T is the gray value of each pixel point before division, and T is a set threshold;
s400: morphological transformation:
(a) and (3) shrinking:
r' denotes the row vectors of the reduced image matrix, R denotes the row vectors of the pre-reduction image matrix, MrowA reduction matrix representing a row direction; c' denotes the column vector of the image matrix after reduction, C denotes the column vector of the image matrix before reduction, McolA reduction matrix representing a column direction;
(b) translation:
g' represents a matrix of the translated image, CfRepresenting a translation matrix, F representing a matrix of the image before translation;
s500: positioning road marking;
processing the image by S300, acquiring points with the processed gray value of 255, namely pixel points of the road marking in the image, acquiring the gray average value of the road marking from the image before processing according to the row and column coordinates of the points, simultaneously taking the center coordinates of the points as the position of the road marking in the image, traversing the stroke of the stepping motor, acquiring the gray values of all the road markings in the range, recording the gray values and the position of the road marking in the image, and acquiring the position with the maximum gray value by sequencing.
8. The image recognition-based road marking alignment system of claim 7, wherein the step of acquiring the image comprises:
s101: using a camera (8) to perform compensation polishing on the road marking;
s102: rapidly acquiring two images which are polished and not polished at the same time;
s103: the interference of other light sources is suppressed,
g is an image after suppressing interference of other light sources, F1For the first image, F2The second image, the first image is a glossy image and the second image is a matte image.
9. The image recognition-based road marking alignment system according to claim 8, wherein the control system obtains the road marking position according to the image processing result, and controls the stepping motor to drive the sliding table (2) so that the camera (8) is aligned with the road marking position.
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